Crash caused by integer conversion to unsigned in TensorFlow
- Published
- Last modified
- Where the record stands: published, rejected by its publisher, or superseded by another id.What do these mean? →
- published
- Whether CISA lists it in its Known Exploited Vulnerabilities catalog: proof that attackers are using it.What do these mean? →
- Not listed in CISA KEV
- Fix
- Fixed in 2.5.1, 2.4.3, 2.3.4
- Whether working attack code is public (Exploit-DB, Metasploit, Nuclei or GitHub). Public code makes attacks easier.What do these mean? →
- None on Exploit-DB, Metasploit or GitHub
Summary
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The implementation does not validate that `num_streams` only contains non-negative numbers. In turn, this results in using this value to allocate memory. However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Timeline
- CVE published
- Record last updated
Affected versions
- tensorflow tensorflow
From 2.5.0 · fixed in 2.5.1; From 2.4.0 · fixed in 2.4.3; fixed in 2.3.4
- tensorflowPyPI
fixed in 2.3.4
- tensorflowPyPI
From 2.4.0 · fixed in 2.4.3
- tensorflowPyPI
From 2.5.0 · fixed in 2.5.1
- tensorflow-cpuPyPI
fixed in 2.3.4
- tensorflow-cpuPyPI
From 2.4.0 · fixed in 2.4.3
- tensorflow-cpuPyPI
From 2.5.0 · fixed in 2.5.1
- tensorflow-gpuPyPI
fixed in 2.3.4
- tensorflow-gpuPyPI
From 2.4.0 · fixed in 2.4.3
- tensorflow-gpuPyPI
From 2.5.0 · fixed in 2.5.1
- tensorflow-cpuPyPI
From 2.3.0 · fixed in 2.3.4; From 2.4.0 · fixed in 2.4.3
- tensorflowPyPI
From 2.3.0 · fixed in 2.3.4; From 2.4.0 · fixed in 2.4.3
- tensorflow-gpuPyPI
From 2.3.0 · fixed in 2.3.4; From 2.4.0 · fixed in 2.4.3